When electronic image data is acquired from an electronic input scanner, it is initially in an analog form. The sensing system of the raster input scanner detects the amount of light reflected from the scanned original and for a discrete area viewed, assigns the sensed light a representative analog value ranging over a continuous scale of values. Upon acquiring this data, the analog information is transformed into a digital approximation of the value, which in many applications may be represented, for example, by an 8 bit data byte, which has a resolution 256 levels of intensity. Since the data derived is indicative of various intensity levels, it must be converted into a format suitable for printing on an output device or display on a soft display device. For example, in a binary printing device, a two level output is required, while other devices allowing printing of more than two levels will require corresponding greater numbers of output levels. Generally, the 8 bit data of varying intensity is directed through a threshold device to determine whether the data for a selected location should be assigned a spot or a blank. The data value for any given pixel location is compared to a threshold value to determine whether a spot should be printed for that location, or if the location should be left blank. In simple applications, particularly for line graphics or text, a single threshold value may be applied to all the data derived by the scanner. Tonal range, contrast and other qualities of the output image may be varied by controlling the threshold conversion applied to the image.
When reproducing continuous tone graphics, such as photographs or paintings, it is often desirable to reproduce the original image grey. To print grey, the printer is directed to modulate the number of spots or intensity of spots within an area, rather than placing all spots or all blanks in the area. The result is perceived as grey. In a binary printer the density of grey is controlled by placing fewer or greater numbers of spots within the same unit of area. Selection of which pixels will appear as either spots or blanks is chosen on the basis of a digital halftone screen or dither matrix. This method has long been used to depict photographic (or continuous tone) inputs. What is accomplished is a synthetically produced grey in order to create a pleasing image. Accurate reproduction or life-like rendition may not always be of interest. Image processing with screening methods can result in images with special effects. These special effects are sometimes desired for eye catching or "artistic" effects. Typically, a screen with predetermined patterns or random dots or lines is used.
Other image processing arrangements offer the opportunity to vary an image and control its ultimate reproduction. Filters work by changing the grey value of each pixel in the electronic image based on various mathematical relationships to one or more pixels in the immediate surrounding area. Filters vary in their function by the relationship employed, by the size of the area covered by the filter and the number of pixels used, and/or coefficient values associated with each pixel. Filters work by emphasizing edges or particular frequencies of interest. Just as there are screens that create special effects in images, there are also filters that create their own type of special effects. Differential filters detect edges in an image, resulting in the output image being an `outlined` version of the original. There are many differential filters useful for edge gradient detection, including one class known as Laplacian operators. Such filters are discussed in Gonzalez & Wintz, Digital Image Processing, Addison-Wesley Publishing Co. Reading, MA p. 58 and p. 212.
Moire is the result of two or more periodic patterns beating or interacting with each other. Patterns here are defined as halftone screens or sampling (i.e., digitizing). Sampling moire is unavoidable. It varies with sampling frequency of the image input device and the input image frequency. It is an artifact of sampling a periodic input. It is common practice to apply screens in making images of pictorial documents, such as photographs or art work, to create the appearance of intermediate levels of grey.
Several methods have been used in the past to mask or minimize moire. A very common way of masking moire is to apply a low pass filter to demodulate high frequencies, before thresholding or rescreening the image. Low pass filters can be used to limit moire because they suppress high frequencies. The drawback with this method is that the sharpness of the resultant image is correspondingly reduced as well. An alternative to this technique uses hardware or software to apply noise (e.g., with random number generator applying random numbers to a screening operation) to the scanned image, as shown for example in U.S. Pat. No. 4,700,235 to Gall, U.S. Pat. No. 4,449,150 to Kato, U.S. Pat. No. 4,578,714 to Sugiura et al., JP-A 56-143766 to Yokomizo and JP-A 56-141667 to Yokomizo. The artificially produced noise breaks up, or masks the structure of the moire patterns eliminating some of the high frequency structure that comprises the moire. The disadvantage of this method is that it can be intolerably slow for software applications and expensive in hardware.
U.S. Pat. No. 4,782,399 to Sato uses filtering of a digital image to eliminate moire effects by processing the image along two channels, a high resolution channel and a low resolution channel, and selecting the channel that produces the best result for particular image data types. U.S. Pat. No. 4,821,109 to Roe describes the use of a probability function which introduces a random element in the choice of elemental areas at the edge of a halftone dot, U.S. Pat. No. 4,819,066 to Miyagi pertains to continuous tone image data processing that attempts to approximate continuous tone images by reproducing the exact density of the original image. U.S. Pat. No. 4,691,343 to Tenenbaum shows a facsimile arrangement which uses an audio carrier signal superimposed on the image information signal to eliminate noise. U.S. Pat. No. 4,691,366 to Fenster et al. teaches image enhancement by filters selected to attenuate noise. U.S. Pat. No. 4,739,413 to Meyer teaches defining pixel density by a value having amplitude and phase. U.S. Pat. No. 4,811,108 to Numakura et al. teaches conversion of a continuous tone image to a halftone image by processing the data so that the density of a control point in the continuous tone image and the density of a corresponding control point in the halftone image are correlated. U.S. Pat. No. 4,811,115 to Lin et al. teaches the use of an approximate auto correlation function to detect the frequency of halftone image data to select the method of handling the data. U.S. Pat. No. 4,817,180 to Cho et al. teaches the filtering in one or two dimensions for detail emphasis. References herein cited are all specifically incorporated by reference for their teachings.